Movie Starts At : 01:33

A comedy of errors takes place when Sanjay and Anjali send their friends Raj and Anjali respectively to spy on each other. Raj and Anjali fall in love with each other but back off assuming the other to be married to their friend. When Raj realises that his love interest Anjali is not his friend's wife he tries to meet her and tell her his feelings, but is shocked to find Anjali engaged to someone else. Will Raj be able to stop Anjali's marriage and tell her the truth?

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Here we are in 2026, and it's been 10 years since the dawn of mainstream commercial applications of deep learning. Back in 2016, a small number of organizations were just starting to use deep learning for small, simple, (and in hindsight) obvious tasks. Who could have guessed what the next ten years would hold? In this talk, Jeremy Howard, who founded the first medical deep learning company, Enlitic (way back in 2014!) will look across industries at the history of how deep learning went mainstream, and changed all of our lives within just 10 short years.

Jeremy Howard
Founder and CEO
Enlitic

Jeremy Howard is a serial entrepreneur, business strategist, developer, and educator. He is the CEO of Enlitic, a startup he founded to use recent advances in machine learning to transform the practice of medicine, and bring modern medical diagnostics to billions of people in the developing world for the first time. He is the youngest faculty member at Singularity University, where he teaches data science, and is also a Young Global Leader with the World Economic Forum. Previously he was the President and Chief Scientist of Kaggle, a community and competition platform for over 150,000 data scientists. Before working at Kaggle, he was the top ranked participant in data science competitions globally, in 2010 and 2011. He founded two successful Australian startups (the email provider FastMail, and the insurance pricing algorithm company Optimal Decisions Group), both of which grew internationally and were sold to large international companies. He started his career in management consulting, working at the world's most exclusive firms, including McKinsey & Co, and AT Kearney (becoming the youngest engagement manager world-wide, and building a new global practice in what is now called "Big Data"). He is also a keen student, for example developing a new system for learning Chinese, which he used to develop usable Chinese language skills in just one year. Jeremy has mentored and advised many startups, and is also an angel investor. He has contributed to a range of open source projects as a developer, and was a regular expert guest on Australia's most popular TV morning news program.

http://dataedge.ischool.berkel....ey.edu/2016/schedule

Suddennagi Batti Ettre Enagutte | JRM Studio | Official 4K Video | JYOTHI RAO MOHITH

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Rehearsal and Workshop- Prakash Dance class

Cast- Vivek Gowda Ramesh, Payal Chengappa, Pratheek Shetty, Gowrav Shetty, Rashika Raj, Chethan Durga, Madhumathi, Anand Ninasum, Dimple Teju, Ajendra LG, Shreyas, Kuni Kumar

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Role playing dimensions, slowly changing dimensions, conformed dimensions, degenerate and junk are some of the types of dimensions that this video speaks about. It gives an insight to each of the types of dimensions.
Topics covered are as follows:
1. Types of dimensions
2. Slowly changing dimensions
3. Conformed dimensions
4. Degenerate dimension
5. Junk dimension
6. Role playing


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This video gives you an introduction to Factor Analysis, with details on how it works and examples.

This video contains the following topics:
00:00 Introduction
01:12 What is Factor Analysis?
02:55 Latent Variables
03:37 Assumptions in Factor Analysis
04:35 Purpose of Factor Analysis
05:28 Types of Factor Analysis
06:32 Issues with Factor Analysis
10:06 Basic Logic of Factor Analysis


📝Feel free to share your experience of Factor Analysis in the comment section below.📝

📢📢 𝐓𝐨𝐩 𝟏𝟎 𝐓𝐫𝐞𝐧𝐝𝐢𝐧𝐠 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐋𝐞𝐚𝐫𝐧 𝐒𝐞𝐫𝐢𝐞𝐬 📢📢

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---------𝐄𝐝𝐮𝐫𝐞𝐤𝐚 𝐎𝐧𝐥𝐢𝐧𝐞 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧---------

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In this video on PMP Certification Full Course, we'll be covering a number of different concepts like project management, project planning, project time, cost quality and communication management, project manager roles, interview questions and much more. With this course, you'll have everything you need to know about Project Management.

00:00 What Is Project Management?
45:46 Project Planning In Project Management
52:29 Project Planning
01:06:49 Project Time Management
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06:57:09 Project Manager Interview Questions And Answers

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The PMP certification is the global gold standard for project management professionals. Keep abreast of the changes in the project management practices updated in PMBOK guide - 6th edition and pass the PMP® exam on your first attempt with Simplilearn’s new PMP course. The course covers new trends, emerging practices, tailoring considerations, and places a greater emphasis on strategic and business knowledge. It also includes a new section on the role of the project manager.

PMP Certification Course Overview
The course covers new trends, emerging practices, tailoring considerations, and core competencies required of a Project Management professional. Placing a greater emphasis on strategic and business knowledge, this course also includes a new section on the role of the project manager in both large and small companies.

PMP Course Key Features:
- 35 contact hours/PDUs
- 8 industry case studies, 20 industry-based scenarios
- 6 hands-on projects, 7 simulation test papers (200 questions each)

Eligibility:
The PMP® certification is an essential professional requirement for senior project manager roles across all industries. The course is best suited for: Project Managers, Associate/Assistant Project Managers, Team Leads/Team Managers, Project Executives/Project Engineers, Software Developers, Any professional aspiring to be a Project Manager.

Pre-requisites:
You should have a secondary degree (i.e. high school diploma, associate’s degree or the global equivalent) with 7,500 hours leading and directing projects along with 35 hours of project management education.OR You should have a four-year degree with 4,500 hours leading and directing projects along with 35 hours of project management education.

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GPT3 & Beyond: Key concepts and open questions in a golden age for natural language understanding

Listen in as Professor Christopher Potts discusses the significance and implications of recent Natural Language Understanding developments including GPT-3. He describes the fundamental building blocks of these systems and describes how we can reliably assess and understand them.

Learn more about the AI Professional Program: https://stanford.io/3kYThd2

View the slides for this webinar here: https://stanford.io/potts-GPT3-webinar2023

#gpt3 #stanfordwebinar


Chapters:
0:00 Opening
00:09 Introduction for Chris Potts
1:09 Chris Potts - Welcome to the webinar
03:43 Quick Demo of GPT-3
06:41 GLUE benchmark
10:26 How can you contribute to NLU in this era of these gargantuan models?
11:44 The last mile problem
13:35 GPT example
14:50 Contrast In-Context learning with the standard paradigm of standard supervision
16:47 What are the mechanisms behind this?
18:18 Why does this work so well?
18:35 Self-Supervision
21:08 The role of human feedback
21:32 Chat GPT Diagram
23:42 Step-by-step reasoning
28:13 LLMs for everything approach
41:29 AI Courses at Stanford
46:28 Predictions about the future

In this tutorial you will learn everything you need to fine tune (train) your GPT-2 Model. By training the model on specific texts you can improve the results quality by a large margin. Fine Tuning your GPT-2 Model is quite easy and can be done in a few simple steps.

First you need to download the repository from Github. After that you need to create a training.txt file including the data on which your model should be trained on. The next step is to convert the file into an npz format from which you can then train the model. After the GPT-2 model has been trained you can then copy the files into your final model and just run the sample code.


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Data Science Week Day-1 will teach you Python and Mathematics for Data Science. You will learn the concepts of Python programming such as loops, conditional statements, object-oriented programming, functions and more. This data science course will make you understand the need for probability, statistics, calculus, and linear algebra for data science.

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What is Data Science?
Data science is the domain of study that deals with vast volumes of data using modern tools and techniques to find unseen patterns, derive meaningful information, and make business decisions. Data science uses complex machine learning algorithms to build predictive models.

Why Python for Data Science?
Python is the most popular programming language for data science and machine learning and provides a collection of libraries such as NumPy, Pandas, matplotlib, scikit learn, etc to analyze data and build prediction models.

Why Mathematics for Data Science?
Mathematics is equally essential for creating efficient models. You need to learn statistics, probability, calculus, and linear algebra for understanding the working of machine learning algorithms.

Why Data Science?
Data science or data-driven science enables better decision making, predictive analysis, and pattern discovery. It lets you:
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Learn how to use Figma Variants to design a scalable mobile app. Variants can streamline your frontend design process by allowing you to group and organize similar components into a single container.

✏️ Ahmet Efeoglu developed this course. Check out his channel: https://www.youtube.com/channe....l/UCSziSLMFFNT4PaRQh

🔗 Tutorial file link: https://www.figma.com/file/FrL....R3t9jZ9X8psPdmztdlh/
🔗 Homework file link: https://www.figma.com/file/8js....2feuv6LdhmvVtBXkC2L/

⌨️ (0:00:18) Intro
⌨️ (0:02:13) Accessing Tutorial and Homework Files
⌨️ (0:04:24) Project Overview
⌨️ (0:05:27) Recommending Personal and freeCodeCamp Channel
⌨️ (0:06:25) Basics Overview
⌨️ (0:08:22) Learning The Frame Functionality
⌨️ (0:10:25) Learning The Autolayout Functionality
⌨️ (0:14:39) Learning The Component Functionality
⌨️ (0:18:55) Learning The Variant Functionality
⌨️ (0:21:42) Creating The Type System
⌨️ (0:28:41) Creating The Color Palette/System
⌨️ (0:35:54) Creating The Icon Set
⌨️ (0:41:34) Creating Input Variants
⌨️ (0:52:23) Creating Large Button Variant
⌨️ (1:00:47) Designing Sign Up and Login Screen
⌨️ (1:18:46) Creating Status Bar Variant
⌨️ (1:23:14) Creating The Filter Variant
⌨️ (1:27:40) Creating Bottom Navigation Variant
⌨️ (1:35:02) Creating Image Card Variant
⌨️ (1:49:27) Updating Input Variant
⌨️ (1:57:31) Designing The Discover Screens
⌨️ (2:15:20) Creating Large Avatar Variant
⌨️ (2:24:05) Creating Small Button Variant
⌨️ (2:32:45) Creating The Benefit Card Variant
⌨️ (2:46:45) Designing Details Screen

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Fritz Haber is the scientist who arguably most transformed the world.
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A huge thanks to Dan Charles for writing a fantastic biography of Fritz Haber, for taking the time to talk to us about it, and providing valuable feedback. This video would not be what it is without his contributions. http://site.danielcharles.us https://ve42.co/Charles

Thanks to Tom de Prinse from Explosions and Fire for helping us with the chemistry of explosives. If you like explosions and/or fire, you will love his channel. https://www.youtube.com/c/ExplosionsFire2

Thanks to Michael Kuiper of CSIRO for the animation of the composition of air - https://www.youtube.com/watch?v=j9JvX58aRfg

Special thanks to Sonya Pemberton, Karl Kruszelnicki, Mary Dobbie, Olivia McRae, and the patreon supporters for giving us feedback on the earlier version of this video.

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References:

The primary reference used is Vaclav Smil’s excellent book, Enriching The Earth –
Smil, V. (2004). Enriching the earth: Fritz Haber, Carl Bosch, and the transformation of world food production. MIT press. – https://ve42.co/Smil

Mastermind: The Rise and Fall of Fritz Haber, the Nobel Laureate Who Launched the Age of Chemical Warfare, by Dan Charles – https://ve42.co/Charles

Stoltzenberg, D. (2004). Fritz Haber: Chemist, Nobel Laureate, German, Jew. Chemical Heritage Foundation. – https://ve42.co/Stoltzenberg

Postgate, J. R. (1982). The fundamentals of nitrogen fixation. CUP Archive. – https://ve42.co/postgate

Miles, A. G. (1992). Biological nitrogen fixation. – https://ve42.co/Miles

Friedrich, B., & Hoffmann, D. (2017). Clara Immerwahr: A life in the shadow of Fritz Haber. In One Hundred Years of Chemical Warfare: Research, Deployment, Consequences(pp. 45-67). Springer, Cham. – https://ve42.co/Friedrich2017

Da Silva, G. (2020). What is ammonium nitrate, the chemical that exploded in Beirut. Sci Am, 5. – https://ve42.co/Silva

Rodrigues, P., & Micael, J. (2021). The importance of guano birds to the Inca Empire and the first conservation measures implemented by humans. – https://ve42.co/rodrigues

Allison, F. E. (1957). Nitrogen and soil fertility. Soil, the, 85-94. – https://ve42.co/Allison

Crookes, W. (1898). Address of the President before the British Association for the Advancement of Science, Bristol, 1898. Science, 8(200), 561-575. – https://ve42.co/Crookes

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Special thanks to Patreon supporters: RayJ Johnson, Brian Busbee, Jerome Barakos M.D., Amadeo Bee, Julian Lee, Inconcision, TTST, Balkrishna Heroor, Chris LaClair, Avi Yashchin, John H. Austin, Jr., OnlineBookClub.org, Matthew Gonzalez, Eric Sexton, john kiehl, Diffbot, Gnare, Dave Kircher, Burt Humburg, Blake Byers, Dumky, Evgeny Skvortsov, Meekay, Bill Linder, Paul Peijzel, Josh Hibschman, Timothy O’Brien, Mac Malkawi, Michael Schneider, jim buckmaster, Juan Benet, Ruslan Khroma, Robert Blum, Richard Sundvall, Lee Redden, Vincent, Stephen Wilcox, Marinus Kuivenhoven, Michael Krugman, Cy 'kkm' K'Nelson, Sam Lutfi, Ron Neal

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Written by Petr Lebedev, Derek Muller, Felicity Nelson and Kovi Rose
Edited by Trenton Oliver
Animation by Jakub Mistek, Fabio Albertelli, Ivy Tello, Alex Drakoulis, Nils Ramses Kullack, and Charlie Davies
SFX by Shaun Clifford
Filmed by Petr Lebedev, Derek Muller and Raquel Nuno
Photo of nitrogen deficiency in rice from https://ve42.co/rice
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Top 20 Most Important Excel Formulas by simplilearn is dedicated to guide the aspiring data analysts and business analysts with the top Excel Formulas For Data Analysis in 2024 and beyond. This Excel tutorial for beginners by Simplilearn will cover the following topics. In this video, we learn into the top 20 to 25 most important Excel formulas every data analyst needs to excel in their role.This excel tutorial will help you to refine your skills, and building a strong foundation in Excel proficiency.

0:00:00 How To Change Lower Case To Upper Case In Excel?
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➡️ About Post Graduate Program In Data Analytics
This Data Analytics Program is ideal for all working professionals and prior programming knowledge is not required. It covers topics like data analysis, data visualization, regression techniques, and supervised learning in-depth via our applied learning model with live sessions by leading practitioners and industry projects.

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This Edureka video on 'Data Exploration - Data Cleaning' is the fifth class in the Python Machine Learning Series which gives a brief introduction to how we can clean the data from redundancies for further processes.

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Class 1 - Introduction To Machine Learning
Class 2 - Statistics For Machine Learning
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Class 4 - Data Exploration 2 - Visualization
Class 5 - Data Exploration 3 - Data Cleaning
[𝐒𝐮𝐧𝐝𝐚𝐲 - 𝟏𝟔𝐭𝐡 𝐀𝐮𝐠𝐮𝐬𝐭]
Class 6 - Data Modeling 1 - Feature Engineering
Class 7 - Data Modeling 2 - Training The Model
Class 8 - Data Modeling 3 - Model Evaluation
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Class 10 - Advanced Machine Learning

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This Machine Learning with Python tutorial gives an introduction to Machine Learning and how to implement Machine Learning algorithms in Python. By the end of this video, you will be able to understand Machine Learning workflow, steps to download Anaconda, types of Machine Learning and hands-on in Python for Linear Regression and K-Means clustering algorithms.


Below are the topics covered in this Machine Learning tutorial:
1. Why Machine Learning? ( 01:09 )
2. Applications of Machine Learning ( 01:50 )
3. How does Machine Learning work? ( 03:33 )
4. Machine Learning Workflow ( 04:53 )
5. Steps to download Anaconda ( 06:13 )
6. Types of Machine Learning ( 09:53 )
7. Linear Regression Demo ( 13:51 )
8. K-Means Clustering Demo ( 26:02 )
9. Use Case - Weather Analysis ( 39:27 )

What is Machine Learning: Machine Learning is an application of Artificial Intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.

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➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features

- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
- Master Classes delivered by Purdue faculty and IBM experts
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- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

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- ChatGPT
- Generative AI
- Explainable AI
- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
- And Many More…

👉 Learn More At:




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In this tutorial, we’ll explore how GitHub Copilot can revolutionize your coding experience. We’ll show you step-by-step how to set it up in Visual Studio Code and use it to build a JavaScript application . From generating code snippets to solving logic problems, Copilot acts as your AI-powered coding partner. Get ready to see how Copilot makes coding faster, smarter, and more fun!

00:00 Introduction
01:35 What is Github Copilot ?
02:31 How does Copilot works ?
01:35 What is Github Copilot ?
04:41 Installing Github Copilot
09:31 Building a Javascript based Application using Github Copilot


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➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more. Join masterclasses led by IITG faculty, engage in hands-on projects, and earn Executive Alumni Status.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered:
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

Learning Path:
✅ IITG AI: Program Induction
✅ IITG AI: Programming Fundamentals
✅ IITG AI: Python for Data Science (IBM)
✅ IITG AI: Applied Data Science with Python
✅ IITG AI: Machine Learning
✅ IITG AI: Deep Learning with TensorFlow (IBM)
✅ IITG AI: Deep Learning Specialization
✅ IITG AI: Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ IITG AI: Advanced Generative AI
✅ IITG AI: Capstone
Electives:
✅ IITG AI: ADL & Computer Vision
✅ IITG AI: NLP and Speech Recognition
✅ IITG AI: Reinforcement Learning
✅ IITG AI: Academic Masterclass
✅ IITG AI: Industry Masterclass

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🔥Advanced Executive Program In Applied Generative AI - https://www.simplilearn.com/applied-generative-ai-course?utm_campaign=QTYkoK_ty7M&utm_medium=Lives&utm_source=Youtube

This Generative AI Full Course 2025 by Simplilearn provides a structured learning path, starting with the fundamentals of Generative AI and a detailed roadmap to mastering it. Learners explore top AI technologies, including DeepSeek R1, Deep Learning, and Search GPT, followed by essential tools like LangChain. The course dives into Generative Adversarial Networks (GANs), Transformers, and Long Short-Term Memory (LSTM) networks, forming the foundation of modern AI models. It then introduces Large Language Models (LLMs), Machine Learning concepts, and Reinforcement Learning, leading into practical applications like ChatGPT analysis and OpenAI Sora. Advanced topics include LLM benchmarking, Hugging Face tutorials, and OpenAI's ChatGPT O1 model. Practical insights into Generative AI tools for job interviews, Agentic AI, and AI monetization strategies help learners stay ahead in the field. The course concludes with a look at Google Quantum AI and Machine Learning interview preparation, ensuring a strong grasp of both theoretical and applied AI concepts.

Following are the topics covered in the Generative AI Full Course 2025:

00:00:00 - Introduction to Gen AI Full Course 2025
00:00:45 - What is Gen AI
00:11:24 - Roadmap Gen AI
01:16:27 - What is Machine Learning
01:23:26 - Deep Learning
01:24:50 - Introduction to LLM
01:47:32 - What are Gen AI Agents
02:24:34 - Agentic AI
03:21:06 - Machine Learning Tutorial
05:26:29 - Reinforcement Learning
05:42:34 - Deepseek r1
05:53:47 - Install Deepseek
06:44:30 - Hugging Face and its tutorial
06:52:47 - Search GPT
06:55:02 - Langchain
07:51:37 - Generative Adversarial Tutorial
09:21:57 - Introduction to agentic workflow
09:31:19 - What are Gans
09:32:20 - Transformers in AI
09:44:49 - LSTM
10:04:40 - CHatgpt analyse
10:15:36 - Openai sora
10:24:29 - LLM Benchmarkeing
10:39:53 - Open ai chatgpt o1 model
10:48:16 - Google Quantam AI
10:53:49 - Majorana
10:58:58 - Gen ai tools for job interview
12:59:19 - Deep learning Interview questions
13:05:13 - Claude 3 sonnet

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➡️ About Professional Certificate Program in Generative AI and Machine Learning

Dive into the future of AI with our Generative AI & Machine Learning course, in collaboration with E&ICT Academy, IIT Guwahati. Learn tools like ChatGPT, OpenAI, Hugging Face, Python, and more.

Key Features:
✅ Program completion certificate from E&ICT Academy, IIT Guwahati
✅ Curriculum delivered in live virtual classes by seasoned industry experts
✅ Exposure to the latest AI advancements, such as generative AI, LLMs, and prompt engineering
✅ Interactive live-virtual masterclasses delivered by esteemed IIT Guwahati faculty
✅ Opportunity to earn an 'Executive Alumni Status' from E&ICT Academy, IIT Guwahati
✅ Eligibility for a campus immersion program organized at IIT Guwahati
✅ Exclusive hackathons and “ask-me-anything” sessions by IBM
✅ Certificates for IBM courses and industry masterclasses by IBM experts
✅ Practical learning through 25+ hands-on projects and 3 industry-oriented capstone projects
✅ Access to a wide array of AI tools such as ChatGPT, Hugging Face, DALL-E 2, Midjourney and more
✅ Simplilearn's JobAssist helps you get noticed by top hiring companies

Skills Covered:
✅ Generative AI
✅ Prompt Engineering
✅ Chatbot Development
✅ Supervised and Unsupervised Learning
✅ Model Training and Optimization
✅ Model Evaluation and Validation
✅ Ensemble Methods
✅ Deep Learning
✅ Natural Language Processing
✅ Computer Vision
✅ Reinforcement Learning
✅ Machine Learning Algorithms
✅ Speech Recognition
✅ Statistics

Learning Path:
✅ Program Induction
✅ Programming Fundamentals
✅ Python for Data Science (IBM)
✅ Applied Data Science with Python
✅ Machine Learning
✅ Deep Learning with TensorFlow (IBM)
✅ Deep Learning Specialization
✅ Essentials of Generative AI, Prompt Engineering & ChatGPT
✅ Advanced Generative AI
✅ Capstone
Electives:
✅ ADL & Computer Vision
✅ NLP and Speech Recognition

👉 Learn More At: https://www.simplilearn.com/iitg-generative-ai-machine-learning-program?utm_campaign=QTYkoK_ty7M&utm_medium=Lives&utm_source=Youtube

Sebastian's books: https://sebastianraschka.com/books/
The lecture slides are available at: https://github.com/rasbt/stat4....53-deep-learning-ss2

Covers some of the more advanced concepts behind convolutional neural networks. In particular, the topics are

- Inception architectures
- Transfer learning

Here are the links to the related, previous videos:
- Intro to CNNs Part 1 https://www.youtube.com/watch?v=7ftuaShIzhc
- Intro to CNNs Part 2 (1/2) https://www.youtube.com/watch?v=mZmyp0JjH6s